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Title: The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations

Abstract

Clouds present many challenges to climate modelling. To develop and verify the parameterisations needed to allow climate models to represent cloud structure and processes, there is a need for high-quality observations of cloud optical depth from locations around the world.Retrievals of cloud optical depth are obtainable from radiances measured by Aerosol Robotic Network (AERONET) radiometers in “cloud mode” using a two-wavelength retrieval method. However, the method is unable to detect cloud phase, and hence assumes that all of the cloud in a profile is liquid.This assumption has the potential to introduce errors into long-term statistics of retrieved optical depth for clouds that also contain ice.Using a set of idealised cloud profiles we find that, for optical depths above 20, the fractional error in retrieved optical depth is a linear function of the fraction of the optical depth that is due to the presence ofice cloud (“ice fraction”). Clouds that are entirely ice have positive errors with magnitudes of the order of 55 % to 70 %. We derive a simple linear equation that can be used as a correction at AERONET sites where ice fraction can be independently estimated. Using this linear equation, we estimate the magnitude of the errormore » for a set of cloud profiles from five sites of the Atmospheric Radiation Measurement programme. The dataset contains separate retrievals of ice and liquid retrievals; hence ice fraction can be estimated. The magnitude of the error at each location was related to the relative frequencies of occurrence in thick frontal cloud at the mid-latitude sites and of deep convection at the tropical sites – that is, of deep cloud containing both ice and liquid particles. The long-term mean optical depth error at the five locations spans the range 2–4, which we show to be small enough to allow calculation of top-of-atmosphere flux to within 10 % and surface flux to about 15 %.« less

Authors:
 [1]; ORCiD logo [2];  [3]; ORCiD logo [4];  [5];  [6]; ORCiD logo [6];  [4]; ORCiD logo [3]
  1. Univ. of Reading (United Kingdom)
  2. Colorado State Univ., Fort Collins, CO (United States)
  3. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
  4. NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Science Systems and Applications, Inc., Lanham, MD (United States)
  5. National Center Univ., Taoyuan (Taiwan)
  6. Univ. of Utah, Salt Lake City, UT (United States)
Publication Date:
Research Org.:
Univ. of Reading, Reading (United Kingdom); Colorado State Univ., Fort Collins, CO (United States); NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); European Union
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1610847
Grant/Contract Number:  
SC0006001; SC0011666; SC0018930; SC0018045; NE/N018486/1
Resource Type:
Accepted Manuscript
Journal Name:
Atmospheric Measurement Techniques (Online)
Additional Journal Information:
Journal Name: Atmospheric Measurement Techniques (Online); Journal Volume: 12; Journal Issue: 9; Journal ID: ISSN 1867-8548
Publisher:
European Geosciences Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Meteorology & Atmospheric Sciences

Citation Formats

Shonk, Jonathan K. P., Chiu, Jui-Yuan Christine, Marshak, Alexander, Giles, David M., Huang, Chiung-Huei, Mace, Gerald G., Benson, Sally, Slutsker, Ilya, and Holben, Brent N. The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations. United States: N. p., 2019. Web. https://doi.org/10.5194/amt-12-5087-2019.
Shonk, Jonathan K. P., Chiu, Jui-Yuan Christine, Marshak, Alexander, Giles, David M., Huang, Chiung-Huei, Mace, Gerald G., Benson, Sally, Slutsker, Ilya, & Holben, Brent N. The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations. United States. https://doi.org/10.5194/amt-12-5087-2019
Shonk, Jonathan K. P., Chiu, Jui-Yuan Christine, Marshak, Alexander, Giles, David M., Huang, Chiung-Huei, Mace, Gerald G., Benson, Sally, Slutsker, Ilya, and Holben, Brent N. Mon . "The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations". United States. https://doi.org/10.5194/amt-12-5087-2019. https://www.osti.gov/servlets/purl/1610847.
@article{osti_1610847,
title = {The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations},
author = {Shonk, Jonathan K. P. and Chiu, Jui-Yuan Christine and Marshak, Alexander and Giles, David M. and Huang, Chiung-Huei and Mace, Gerald G. and Benson, Sally and Slutsker, Ilya and Holben, Brent N.},
abstractNote = {Clouds present many challenges to climate modelling. To develop and verify the parameterisations needed to allow climate models to represent cloud structure and processes, there is a need for high-quality observations of cloud optical depth from locations around the world.Retrievals of cloud optical depth are obtainable from radiances measured by Aerosol Robotic Network (AERONET) radiometers in “cloud mode” using a two-wavelength retrieval method. However, the method is unable to detect cloud phase, and hence assumes that all of the cloud in a profile is liquid.This assumption has the potential to introduce errors into long-term statistics of retrieved optical depth for clouds that also contain ice.Using a set of idealised cloud profiles we find that, for optical depths above 20, the fractional error in retrieved optical depth is a linear function of the fraction of the optical depth that is due to the presence ofice cloud (“ice fraction”). Clouds that are entirely ice have positive errors with magnitudes of the order of 55 % to 70 %. We derive a simple linear equation that can be used as a correction at AERONET sites where ice fraction can be independently estimated. Using this linear equation, we estimate the magnitude of the error for a set of cloud profiles from five sites of the Atmospheric Radiation Measurement programme. The dataset contains separate retrievals of ice and liquid retrievals; hence ice fraction can be estimated. The magnitude of the error at each location was related to the relative frequencies of occurrence in thick frontal cloud at the mid-latitude sites and of deep convection at the tropical sites – that is, of deep cloud containing both ice and liquid particles. The long-term mean optical depth error at the five locations spans the range 2–4, which we show to be small enough to allow calculation of top-of-atmosphere flux to within 10 % and surface flux to about 15 %.},
doi = {10.5194/amt-12-5087-2019},
journal = {Atmospheric Measurement Techniques (Online)},
number = 9,
volume = 12,
place = {United States},
year = {2019},
month = {9}
}

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